Diauxic shift of Roseburia intestinalis

Enables slow growth after depletion of glucose

R. intestinalis Adapts via Diauxic Shift

Mechanism of Survival

  • Slow-Growth Mode: R. intestinalis survives depletion of glucose and mucin products by drastically reducing growth rate.
  • Metabolic Switch: Metabolomics & RNA-seq confirm a diauxic shift toward consuming:
    • Acetate
    • Lactate

Gene Expression

Consistent upregulation observed in: * Sugar utilization pathways (glycolysis, pyruvate utilization) * Butyrate-producing pathways

Source: Liu, B., Garza, D.R., Gonze, D. et al. (2023).
Starvation responses impact interaction dynamics of human gut bacteria…
ISME Journal 17. DOI: 10.1038/…

Data overview

  • Fermentation

    • containing 888 experiments with data:
    • Exp, Replicate, Mucin, Species.combi, T0h, T4h, T6h, T8h, T10h, T12h, T14h, T16h, T20h, T24h, T28h, T32h, T36h, T38h, T40h, T42h, T44h, T48h, T56h, T60h, T72h, T86h, T96h, T120h, T144h, T156h, T168h, T192h, T216h, T240h, T264h, T288h

  • RNA expression data

    • containing recorded expression of 4262 genes in 45 experiments

  • Annotation for expression dataset

    • Coupling internal gene ID’s to gene names , KO ID’s, and COG ID’s

  • Meta-data for fermentation dataset

    • Coupling RNA expression samples with fermentation batches and time points

Data Cleaning and Augmentation

Removing empty time-points from fermentation dataset

ri_fermentation_data |>
  filter(Exp == "RI_batch_WC1") |>
  select( "Rowname", (starts_with("T") & ends_with("h")) ) |>
  select(where(~!all(is.na(.x)) ) ) |>
  write_csv("../data/02_fermentation_data_clean.csv")

Subsetting RNA expression to wild type R. intestinalis only

ri_expression_data |> 
  pivot_longer(cols = -X,
               
               names_to = "sample",
               values_to = "expression") |> 
  inner_join(ri_metadata, by = c("sample" = "GC.code" )) |> 
  filter(Exp == "RI_batch_WC") |> 
  select(X,expression,sample) |> 
  pivot_wider(names_from = sample,
              values_from = expression) |> 
  write_csv("../data/02_data_clean.csv")

Correlation Matrix from Gene Expression data

  • Input data was a total of 9 samples across 3 time conditions
  • Matrix reveals co-expression patterns in R. intestinalis gene expression data
  • Co-regulated genes can potentially contribute to the same pathways

K-Means Identifies 3 Distinct Clusters

  • Methodology: Applied K-means clustering to the correlation matrix.
  • Observation: Genes show clear separation in 2D PCA space.

Note: The cutoff for 3 clusters was selected for regulation validation purposes.

Figure 1: PCA Projection of Gene Clusters

Pathway Enrichment Reveals Distinct Cluster Functions

Observations

  • Major pathways (top bars) are shared across all three clusters.
  • Certain pathways are exclusive to Cluster 1 or 2 (e.g., lower yellow/green bars).

Differential Expression Analysis

  • This volcano plot visualizes the transcriptional changes that R. intestinalis undergoes during the transition.

  • The highly upregulated genes reflect the shift toward alternative energy sources needed after glucose depletion, including pathways for acetate and lactate consumption.

  • The highly downregulated genes correspond to pathways that are no longer prioritized once glucose is exhausted, particularly those involved in glucose and pyruvate utilization.

Dynamic Regulation of Key Genes

  • Visualizing Change: These 6 genes represent the most significant expression changes identified in the RNA-seq analysis across time points (4h, 12h, 48h).
  • Distinct Phases:
    • Early Expression (Red/Green): Genes essential for initial rapid growth.
    • Late Shifts (Blue): Genes that spike at 48h likely drive the diauxic shift and survival maintenance.

R. intestinalis Exhibits Metabolic Resilience

1. Survival Stability Active cell counts remain stable even after nutrient depletion.

2. Fermentation Dynamics Butyrate continues rising as glucose is exhausted.

Conclusions

  • 1. Functional Architecture
    • Gene co-expression matrix analysis, K-means clustering, and enrichment analysis reveal a structured functional organization within the genome.
  • 2. Metabolic Flexibility
    • The diauxic shift to acetate and glucose consumption is supported, both by RNA-seq and fermentation data.
    • This metabolic switch enables a “slow-growth” maintenance mode, allowing R. intestinalis to maintain cell viability and continue producing butyrate.